ISSN 打印: 2152-5080
卷:卷 7, 2017 卷 6, 2016 卷 5, 2015 卷 4, 2014 卷 3, 2013 卷 2, 2012 卷 1, 2011
Algorithms for interval neutrosophic multiple attribute decision making based on MABAC, similarity measure and EDAS
In this paper, we define a new axiomatic definition of interval neutrosophic similarity measure, which is presented by interval neutrosophic number (INN). Later, the objective weights of various attributes are determined via Shannon entropy theory, meanwhile, we develop the combined weights, which can show both the subjective information and the objective information. Then, we present three approaches to solve interval neutrosophic decision making problems by Multi-Attributive Border Approximation area Comparison (MABAC), Evaluation based on Distance from Average Solution (EDAS) and similarity measure. Finally, the effectiveness and feasibility of algorithms are conceived by two illustrative examples.
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